Artificial Intelligence & Data Science Graduate

Hi, I'm Momen Hamza

A recent graduate in Artificial Intelligence and Data Science with a strong foundation in machine learning, deep learning, computer vision, and data analysis. I build intelligent systems using Python, TensorFlow, Scikit-learn, and YOLOv8 to solve real-world problems.

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AI Projects in Machine Learning, Deep Learning, and Computer Vision

About Me

Hello! I'm Momen Hamza, a recent graduate in Computer Science and Artificial Intelligence with a strong interest in machine learning, deep learning, computer vision, and data analysis.

I graduated from Tafila Technical University and built hands-on experience through academic and practical projects in predictive modeling, intelligent systems, and AI-powered applications.

I enjoy solving real-world problems using Python, TensorFlow, Scikit-learn, and modern AI tools. My graduation project focused on developing a smart detection system for visually impaired users using YOLOv8, Streamlit, and Arabic voice guidance.

Technologies I Work With

PythonMachine LearningDeep LearningTensorFlowScikit-learnComputer VisionData AnalysisNatural Language ProcessingYOLOv8Streamlit

2025

Graduate

5

Projects

2

Courses

AI

Focus

Technical Skills

My technical background in artificial intelligence, data science, and modern development tools.

Machine Learning & AI

Machine Learning90%

Deep Learning85%

Neural Networks85%

TensorFlow80%

Data Science & Analysis

Data Analysis88%

Predictive Modeling84%

Scikit-learn85%

Problem Solving90%

Computer Vision & Development

Computer Vision85%

YOLOv880%

Python92%

Streamlit78%

Featured Projects

A selection of my academic and practical projects in artificial intelligence, machine learning, and data analysis.

PythonViTWav2Vec2Deep LearningMultimodal

Voice & Facial Emotion Recognition System

Built a multimodal emotion recognition system that fuses facial expression analysis (ViT) and voice emotion analysis (Wav2Vec2) to detect emotions such as happy, sad, angry, fearful, and neutral. Trained on RAVDESS, CREMA-D, FER2013, and TESS datasets using MFCC and prosody features, with a live demo for real-time inference.

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PythonNLPIntent ClassificationNERGradio

Multilingual Intent & NER Chatbot

Developed a multilingual chatbot supporting Arabic, English, French, and code-switching. The system automatically detects language, classifies 6 intents (booking, complaint, farewell, greeting, inquiry, other), extracts named entities (names, places, dates), and retrieves relevant answers to reply naturally. Built with a Gradio interface.

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PythonYOLOv8Deep LearningStreamlit

Smart Detection Prototype for the Visually Impaired

Developed a real-time assistive system for visually impaired users using YOLOv8 and deep learning. The system detects traffic signs, obstacles, pedestrians, and stairs, then provides Arabic voice instructions for object type, direction, and distance. Built with Python and Streamlit using a custom dataset with annotation, balancing, and augmentation.

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PythonCNNDeep LearningComputer VisionMRI

Brain Tumor Classification

Built a deep learning model using CNNs to detect and classify brain tumors (Glioma, Meningioma, Pituitary, and No Tumor) from MRI images. Trained on a labeled dataset of 5.6k training and 1.6k test scans, with a live demo deployed on Hugging Face Spaces for real-time inference.

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PythonMachine LearningScikit-learnData Analysis

Heart Disease Prediction

Developed a machine learning model to classify patients based on health data and predict heart disease risk.

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PythonMachine LearningClassificationData Analysis

Customer Behavior Analysis

Classified customers based on age, order history, and income to predict purchasing decisions.

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PythonData AnalysisVisualizationInsights

Laptop Characteristics and Price Analysis

Analyzed and visualized laptop features and prices to help customers make informed buying decisions.

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